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Using Machine Learning

Posted on September 5, 2017 by admin Posted in Software Leave a comment

What it is: Pixelmator announced a new professional graphics editor called Pixelmator Pro that uses machine learning.

For the longest time, Adobe Photoshop ruled the graphics editing world. The problem of Photoshop was that it was expensive, it was cross-platform for Windows and macOS so it wasn’t really optimized for either operating system, and Adobe switched to a subscription model so you had to buy a software subscription to use Photoshop. For many graphics professionals, Photoshop is the only alternative.

However, Pixelmator is a low-cost alternative graphics editor that does much of what most people need. Now the company that brought Pixelmator has introduced a new professional version called Pixelmator Pro. Although the cost hasn’t been revealed yet, one unique feature is that Pixelmator Pro uses Apple’s latest machine learning features. Presumably this machine learning feature will allow Pixelmator Pro to help people edit images faster and more accurately than before, but this could be the first major use of machine learning in a major application so it will be interesting to see how well it works.

The real key to machine learning isn’t just to use trained models but to allow users to train and update the machine learning model through use of the program. While this likely isn’t possible yet, it’s what will make machine learning far more valuable to adapt to the user rather than offer a canned response every time.

Pixelmator Pro offers real competition to Adobe Photoshop, and machine learning just makes this program even more intriguing. Best of all, Pixelmator Pro is optimized solely for macOS so it should run better and faster than Adobe Photoshop. The only question is whether Pixelmator Pro can offer all the features professional graphics users need.

Whatever the case, the graphics editing world is getting full of rivals and alternatives to Photoshop. Beyond Pixelmator Pro, there’s Affinity Photo along with Adobe’s own Photoshop Elements, a simpler version of Photoshop for the average person.

Photoshop may be the dominate graphics editor today and maybe even tomorrow, but now you won’t have to rely on Photoshop any more if you don’t want to. Pixelmator Pro will be coming this fall and this may give you a chance to leave Photoshop once and for all.

To learn more about Pixelmator Pro, click here.

Apple AI Researchers Win Prestigious Award

Posted on August 26, 2017 by admin Posted in Programming, Software Leave a comment

What it is: Artificial intelligence (AI) researchers at Apple recently won a Best Paper Award at the 2017 Conference on Computer Vision & Pattern Recognition, one of the most sought after prizes in the field.

For the longest time, Apple refused to let their researchers publish papers. The rationale behind this was to keep the competition from following what Apple was doing, but the drawback to this was that many AI researchers refused to work at Apple because they didn’t want to keep their research private. Many researchers also wondered whether secrecy could actually hurt Apple by keeping their researchers from sharing ideas with others in the AI field.

Eventually, Apple let their researchers publish papers and in the first year of submitting papers, Apple researchers won a Best Paper Award for a computer vision paper. What’s notable about this award is that it proves that Apple isn’t behind in AI research as many critics have suggested.

Google has been testing self-driving cars for years, long before Apple started so people naturally thought Google has an insurmountable lead. While starting early can be a benefit, such an early head start can be lost if researchers from other companies come up with more creative and innovative solutions. AI research isn’t a matter of starting first and assuming you’ll always stay ahead forever. AI research is a new field that everyone is studying so there’s no fixed way to insure a lead in any part of AI research.

Spending more money and hiring more researchers won’t always be the answer because smaller teams of researchers with less money can still find an innovative solution that larger, better funded teams may overlook. AI research is a brand new field that’s ripe for pioneers from everywhere. The fact that Google got started with self-driving cars earlier than most everyone else is an advantage, but not an insurmountable one. Chances are good that researchers all over the world are ahead of Google in certain areas of autonomous technology while Google is ahead of everyone else in other areas.

Apple was first in commercially developing natural voice language processing with Siri, but despite being first, Amazon and Google seem to have caught up. Still, Siri has the advantage in recognizing more languages than its rivals, but its rivals appear better at understanding the context of spoken commands better.

So it’s likely that AI research will continue advancing from all different companies. Expect Apple to continue promoting AI. Already Apple is promoting machine learning for creating apps but this is just a first step. Right now, Apple’s machine learning option lets you take a trained machine learning file and use it. However, this trained machine learning file seems fixed. Once you use it, it never learns again. In the future, expect Apple to allow your apps to create their own machine learning models and constantly modify and improve its features.

AI is coming to smartphone and tablet apps along with computer programs for Windows and macOS. AI is the next rapidly growing field of the computer industry so expect to see more companies throwing around the terms of artificial intelligence on their products. AI is going to be a crucial element of software and computer development in the future. Apple’s latest prize award simply shows that Apple is not behind its rivals in AI research after all.

States Moving on Self-Driving Vehicle Legislation

Posted on August 4, 2017 by admin Posted in Hardware, Software Leave a comment

What it is: Nevada is one of many states crafting laws to anticipate self-driving vehicles.

By the time the Federal government reacts, it’s usually too late. That’s why many states such as Nevada have already crafted legislation to deal with self-driving vehicles. States already can see the future that self-driving technology will be the future and they want to attract self-driving technology companies to test and deploy vehicles in their states to bring in revenue. While self-driving passenger cars may be the ultimate dream, it’s far likely that self-driving vehicles will appear much sooner in other areas.

One simple application of self-driving vehicles is within a limited domain such as a shuttle bus. By traversing a known road, self-driving technology just needs to deal with pedestrians and unexpected hazards like fallen trees or stalled vehicles. Otherwise a limited domain gives a self-driving vehicle a much greater chance of working properly.

Another possibility is self-driving long-distance trucks. Right now, long-distance trucks navigate highways, which are relatively simple with few pedestrians to worry about. The idea is to let self-driving technology handle long hauls across highways and then let human drivers handle the actual driving within streets leading to the ultimate loading or unloading area. Right now truck drivers are limited by the need to sleep, but self-driving technology would let drivers sleep while the truck drives itself across the highway at night where there would be fewer cars. This would allow trucks to drive themselves all night while the human driver sleeps.

Inevitably, self-driving technology will fail and kill someone. That’s why states need to pass legislation now for liability issues so self-driving technology doesn’t get stopped in the courts. Self-driving technology won’t be perfect, but it can be better than human drivers that cause accidents and kill more people than self-driving technology will ever do.

Many people predict that self-driving technology will arrive within ten to twenty years. Expect that to happen in half the time, but in limited environments such as shuttle buses or long-distance trucks. The self-driving world is coming soon and that’s going to uproot the current car industry such as car insurance companies, car dealers, and taxi cabs. Combine self-driving cars with ride-sharing and you get a future where today’s current car market simply won’t exist any more.

The future is coming and it’s clear. All you need to do is set aside your beliefs and see the future clearly without prejudice.

Apple Partners with Hertz

Posted on June 26, 2017 by admin Posted in Hardware, Software Leave a comment

What it is: Apple partnered with Hertz while Google partnered with Avis to pursue self-driving technology.

Both Apple and google have new partners in the self-driving car market. Google already signed a partnership with Avis while Apple just signed an agreement with Hertz. What both companies plan to do with these partnerships remains a mystery, but it’s a safe bet that it involves self-driving cars.

Most likely, neither Hertz nor Avis will rent out self-driving cars. What they will likely do is test self-driving car technology to provide data for Apple and Google. Since self-driving technology relies on machine learning, the more data both companies can collect, the better the self-driving technology will get.

Keep in mind that Apple invested $1 billion dollars on China’s ride-sharing service, Didi Chuxing, which provides more rides per day in China than any other ride-sharing service in the world including Uber. Apple likely doesn’t care about ride-sharing as much as they care about collecting driving data from one of the most congested parts of the world. Since self-driving technology will eventually reach ride-sharing services, Apple’s investment in Didi Chuxing simply gives it access to more driving data than any other company.

The leap to self-driving cars will come slowly. For specific uses such as shuttles around a predictable track, self-driving technology can work today. For general use of most people driving around the streets of today, self-driving technology can only work as assisted-driving technology where the driver remains in control, but computers provide assistance when necessary. For example, if the computer determines that your car will collide with another one, it can automatically slam on the brakes.

Assisted-driving will come today while self-driving technology will come tomorrow. Both Apple and Google are simply planning for the long-term future. It won’t pay dividends now or even in the next five years, but it is the future. In the meantime, Microsoft doesn’t appear to have any self-driving technology research going on, which means Microsoft will miss out on the self-driving market when it finally arrives.

It’s not hard to see the future if you only look. What’s hard is looking for the future and then taking time now to plan for it despite not getting immediately benefits. Apple and Google are planning far head. Other companies are not. Can you guess who will survive in the future?

The Future is Machine Learning

Posted on June 12, 2017 by admin Posted in Programming Leave a comment

What it is: Apple released a new software framework to enable machine learning.

Machine learning has taken the promise of artificial intelligence and made it practical. In the early days of artificial intelligence (AI), programmers had to explicitly write code to mimic intelligence. That meant anticipating every possible outcome, which made early AI projects like expert systems ultimately unwieldy and impractical. Machine learning simplifies AI by defining rules that the computer follows to learn from real-world data.

Credit card companies have been using machine learning to identify possible fraud in credit cards by noticing unusual patterns. If you live in Dallas, Texas but the credit card company suddenly notices purchases made in Miami, Florida and then another in Portland, Oregon that same day, that’s clear something could be wrong.

Spam filters also use machine learning to identify possibly spam and get better at filtering it out. As you identify junk mail, the spam filter learns what you consider spam and gets better at detecting and blocking it ahead of time.

Now machine learning is poised to break through to common computing tasks. Google is adding machine learning to their spreadsheet and Apple is applying machine learning to vision recognition and natural language processing. Vision recognition will help identify faces and objects in a picture while natural language processing will help Siri learn from spoken commands and allow virtual keyboards to offer suggestions based on what you’ve been searching or typing recently.

By offering machine learning as a software framework, Apple has made it easy for developers to add machine learning capabilities to their own apps. Apple is also rumored to be developing a dedicated neural network processor. Combine this neural processor with their machine learning framework and you can see that in the near future (think this fall with the new iPhone), Apple products will include machine learning capabilities that will surpass rival products that still depend on the cloud (Internet) for machine learning tasks.

Apple is moving machine learning to the device itself. One useful example will be language translation. Siri can translate English to several languages including French, Italian, German and Mandarin. It’s only a matter of time before Siri will be able to translate other languages into English as well. By processing this data locally without the need for an Internet connection, an iPhone can be a portable language translation device people can use anywhere in the world.

Machine learning is the future and Apple’s goal of creating a dedicated AI chip makes perfect sense to process this data rapidly on the device itself. That means tomorrow’s iPhone will not only include a general purpose ARM processor but also a graphics processor and an AI processor. Machine learning is going to be the future of mobile computing and Apple is leading the way.

Machine learning is simply the future of computing. It’s going to help widen the gap between Apple products and rivals to such an extent that it will be like comparing a word processor to a typewriter. Both will be able to type but which one will be more efficient and easier to use?

While Amazon and Google forge ahead with virtual assistants that gobble up market share, they’re missing one key element. Both Amazon and Google’s virtual assistants only understand a handful of languages. Siri understands far more languages and that means Siri will become the standard virtual assistant around most of the world.

The future is clear. Machine learning is what will separate tomorrow’s apps from today’s apps. The difference will be as vast as night and day.

Apple’s Satellites

Posted on April 22, 2017 by admin Posted in Business, Hardware Leave a comment

What it is: Apple recently hired two satellite specialists from Google. The big question is why?

Most companies don’t own their own satellites or even care anything about them. If a company needs services that a satellite provides, they can just buy those services from a vendor who takes care of all the details about running and managing a satellite in orbit. Yet Apple recently hired two satellite experts away from Google. Why would Apple need their own satellite experts?

Satellites can be used for mapping, but it’s far cheaper to simply buy satellite imagery from another company rather than hire your own satellite experts. What’s likely he reason Apple wants satellite expertise is because Apple needs satellites for communication.

When Apple first came up with the iPhone, Steve Jobs actually wanted to have it run on its own network. Since that proved impossible at the time, Apple had to partner with a limited number of carriers such as AT&T in the United States. These carriers often created a poor user experience for these early iPhone users, but as more carriers offered the iPhone, fewer people complained about their carriers when using an iPhone.

So one possible reason Apple wants their own satellite experts is to create their own communication network. This could provide better coverage in rural areas without putting up cellular towers everywhere. A big bonus would be that Apple could control the total iPhone experience and cut the traditional wireless carriers out of the loop.

A second, more likely reason is that Apple plans to develop a self-driving car platform. That means constant communication with an Apple Car no matter where it goes on the roads. Since many roads go through rural areas where cellular phone coverage isn’t available, satellite coverage may be the only option.

Self-driving cars rely on artificial intelligence and artificial intelligence relies on collecting as much data as possible to learn from. Voice assistants like Siri rely on a cellular network to send data for collection and processing to a server. This server then sends the results back to the user’s Siri-powered device such as an iPhone or iPad. This keeps the processing of natural languages on servers, freeing up processing power and storage space on the user’s device.

Self-driving cars using machine learning will be no different. Early self-driving cars aren’t likely going to have a supercomputer on board to process driving data. Instead, self-driving cars will stay connected to a server to provide that server with driving data. Then that server will gradually get smarter about driving and provide each self-driving car on the road with improved algorithms for driving.

So Apple’s satellite interests likely lie in self-driving cars. Of course, such as network could also double as a distinct worldwide carrier network of its own, which Apple is likely eyeing at the same time, but the more immediate use for satellites will be for self-driving cars.

Self-driving cars are coming faster than people expect. By developing expertise in satellites today, Apple is preparing for the inevitable future. After all, controlling as much of your product as possible is Apple’s goal, so an Apple satellite network seems likely in the near future for both making phone calls and machine learning for self-driving cars.